Key players and team play: anaerobic microbial communities in hydrocarbon-contaminated aquifers

Biodegradation of anthropogenic pollutants in shallow aquifers is an important microbial ecosystem service which is mainly brought about by indigenous anaerobic microorganisms. For the management of contaminated sites, risk assessment and control of natural attenuation, the assessment of in situ biodegradation and the underlying microbial processes is essential. The development of novel molecular methods, “omics” approaches, and high-throughput techniques has revealed new insight into complex microbial communities and their functions in anoxic environmental systems. This review summarizes recent advances in the application of molecular methods to study anaerobic microbial communities in contaminated terrestrial subsurface ecosystems. We focus on current approaches to analyze composition, dynamics, and functional diversity of subsurface communities, to link identity to activity and metabolic function, and to identify the ecophysiological role of not yet cultured microbes and syntrophic consortia. We discuss recent molecular surveys of contaminated sites from an ecological viewpoint regarding degrader ecotypes, abiotic factors shaping anaerobic communities, and biotic interactions underpinning the importance of microbial cooperation for microbial ecosystem services such as contaminant degradation.     

The response of macroinvertebrate community taxa and functional groups to pollution along a heavily impacted river in Central Europe (Bílina River,Czech Republic)

Macroinvertebrate communities were investigated along a gradient of heavy industrial and municipal pollution in the highland Bílina River (Czech Republic). Physico-chemical determinants and ions were monitored and community analysis performed focusing on taxonomic composition, ecological functioning (feeder and dweller guilds) and water quality metrics, including saprobity index, BMWP and diversity. Impacted sites differed significantly from reference and from recovered stretches. Chemical data revealed two main pollution factors, (1) a “salinity determinant”, described best by conductivity and SO₄²⁻, and (2) an “organic pollution determinant”, represented best by O₂ concentrations and NO₂⁻, all varying locally and temporally. Some metrics and taxa showed significant correlations to abiotic parameters. Functional communities showed a stronger relationship to the “organic pollution determinant”, suggesting that elevated organic pollution had a dominating influence on functional community metrics; though other variables may also have an influence in this multistress environment. On the other hand, there were indications that the taxonomic community was more influenced by ion concentrations (“salinity determinant”). The gradient from reference sites to polluted sites was weaker in the final sampling campaign. The results presented here can be used as a reference for assessing future changes in environmental impact from pollution, being finer and more detailed than assessment according to the EU’s WFD.     

Novel strain-level resolution of Crohn’s disease mucosa-associated microbiota via an ex vivo combination of microbe culture and metagenomic sequencing

The mucosa-associated microbiota is widely recognized as a potential trigger for Crohn’s disease pathophysiology but remains largely uncharacterised beyond its taxonomic composition. Unlike stool microbiota, the functional characterisation of these communities using current DNA/RNA sequencing approaches remains constrained by the relatively small microbial density on tissue, and the overwhelming amount of human DNA recovered during sample preparation. Here, we have used a novel ex vivo approach that combines microbe culture from anaerobically preserved tissue with metagenome sequencing (MC-MGS) to reveal patient-specific and strain-level differences among these communities in post-operative Crohn’s disease patients. The 16 S rRNA gene amplicon profiles showed these cultures provide a representative and holistic representation of the mucosa-associated microbiota, and MC-MGS produced both high quality metagenome-assembled genomes of recovered novel bacterial lineages. The MC-MGS approach also produced a strain-level resolution of key Enterobacteriacea and their associated virulence factors and revealed that urease activity underpins a key and diverse metabolic guild in these communities, which was confirmed by culture-based studies with axenic cultures. Collectively, these findings using MC-MGS show that the Crohn’s disease mucosa-associated microbiota possesses taxonomic and functional attributes that are highly individualistic, borne at least in part by novel bacterial lineages not readily isolated or characterised from stool samples using current sequencing approaches.Subject terms: Biomarkers, Microbiome, Next-generation sequencing, Clinical microbiology, Metagenomics     

Metagenomic microbial community profiling using unique clade-specific marker genes

Metagenomic shotgun sequencing data can identify microbes populating a microbial community and their proportions, but existing taxonomic profiling methods are inefficient for increasingly large data sets. We present an approach that uses clade-specific marker genes to unambiguously assign reads to microbial clades more accurately and >50× faster than current approaches. We validated our metagenomic phylogenetic analysis tool, MetaPhlAn, on terabases of short reads and provide the largest metagenomic profiling to date of the human gut. It can be accessed at http://huttenhower.sph.harvard.edu/metaphlan/.     

Functional trait assembly through ecological and evolutionary time

A classic community assembly hypothesis is that all guilds must be represented before additional species from any given guild enter the community. We conceptually extend this hypothesis to continuous functional traits, refine the hypothesis with an eco-evolutionary model of interaction network community assembly, and compare the resultant continuous trait assembly rule to empirical data. Our extension of the “guild assembly rule” to continuous functional traits was rejected, in part, because the eco-evolutionary model predicted trait assembly to be characterized by the expansion of trait space and trait/species sorting within trait space. Hence, the guild rule may not be broadly applicable. A “revised” assembly rule did, however, emerge from the eco-evolutionary model: as communities assemble, the range in trait values will increase to a maximum and then remain relatively constant irrespective of further changes in species richness. This rule makes the corollary prediction that the trait range will, on average, be a saturating function of species richness. To determine if the assembly rule is at work in natural communities, we compared this corollary prediction to empirical data. Consistent with our assembly rule, trait “space” (broadly defined) commonly saturates with species richness. Our assembly rule may thus represent a general constraint placed on community assembly. In addition, taxonomic scale similarly influences the predicted and empirically observed relationship between trait “space” and richness. Empirical support for the model’s predictions suggests that studying continuous functional traits in the context of eco-evolutionary models is a powerful approach for elucidating general processes of community assembly.     

Hybridization of genomic DNA to microarrays: a challenge for the analysis of environmental samples

The use of DNA microarrays for detection and identification of bacteria and genes of interest from various environments (e.g. soil, sediment, water column...) is a major challenge for microbiologists working on functional diversity. So far, most of the genomic methods that have been described rely on the use of taxonomic markers (such as 16S rRNA) that can be easily amplified by PCR prior to hybridization on microarrays. However, taxonomical markers are not always informative on the functions present in these bacteria. Moreover, genes for which sequence database is limited or that lack any conserved regions will be difficult to amplify and thus to detect in unknown samples. Furthermore, PCR amplification often introduces biases that lead to inaccurate analysis of microbial communities. An alternative solution to overcome these strong limitations is to use genomic DNA (gDNA) as target for hybridisation, without prior PCR amplification. Though hybridization of gDNA is already used for comparative genome hybridization or sequencing by hybridization, yet to the high cost of tiling strategies and important data filtering, its adaptation for use in environmental research poses great challenges in terms of specificity, sensitivity and reproducibility of hybridization. Considering the very faint number of publications that have described hybridization of gDNA to microarrays for environmental applications, we confront in this review the different approaches that have been developed so far, and propose alternative strategies that may contribute to improve the development of microarrays for studying the microbial genetic structure and composition of samples of high environmental and ecological value.     

Rapid quantitative profiling of complex microbial populations

Diverse and complex microbial ecosystems are found in virtually every environment on earth, yet we know very little about their composition and ecology. Comprehensive identification and quantification of the constituents of these microbial communities—a ‘census’—is an essential foundation for understanding their biology. To address this problem, we developed, tested and optimized a DNA oligonucleotide microarray composed of 10 462 small subunit (SSU) ribosomal DNA (rDNA) probes (7167 unique sequences) selected to provide quantitative information on the taxonomic composition of diverse microbial populations. Using our optimized experimental approach, this microarray enabled detection and quantification of individual bacterial species present at fractional abundances of <0.1% in complex synthetic mixtures. The estimates of bacterial species abundance obtained using this microarray are similar to those obtained by phylogenetic analysis of SSU rDNA sequences from the same samples—the current ‘gold standard’ method for profiling microbial communities. Furthermore, probes designed to represent higher order taxonomic groups of bacterial species reliably detected microbes for which there were no species-specific probes. This simple, rapid microarray procedure can be used to explore and systematically characterize complex microbial communities, such as those found within the human body.     

Ecosystem properties and microbial community changes in primary succession on a glacier forefront

We studied microbial community composition in a primary successional chronosequence on the forefront of Lyman Glacier, Washington, United States. We sampled microbial communities in soil from nonvegetated areas and under the canopies of mycorrhizal and nonmycorrhizal plants from 20- to 80-year-old zones along the successional gradient. Three independent measures of microbial biomass were used: substrate-induced respiration (SIR), phospholipid fatty acid (PLFA) analysis, and direct microscopic counts. All methods indicated that biomass increased over successional time in the nonvegetated soil. PLFA analysis indicated that the microbial biomass was greater under the plant canopies than in the nonvegetated soils; the microbial community composition was clearly different between these two types of soils. Over the successional gradient, the microbial community shifted from bacterial-dominated to fungal-dominated. Microbial respiration increased while specific activity (respiration per unit biomass) decreased in nonvegetated soils over the successional gradient. We proposed and evaluated new parameters for estimating the C use efficiency of the soil microbial community: “Max” indicates the maximal respiration rate and “Acc” the total C released from the sample after a standard amount of substrate is added. These, as well as the corresponding specific activities (calculated as Max and Acc per unit biomass), decreased sharply over the successional gradient. Our study suggests that during the early stages of succession the microbial community cannot incorporate all the added substrate into its biomass, but rapidly increases its respiration. The later-stage microbial community cannot reach as high a rate of respiration per unit biomass but remains in an “energy-saving state,” accumulating C to its biomass. Received: 4 June 1998 / Accepted: 11 January 1999     

RiboTagger: fast and unbiased 16S/18S profiling using whole community shotgun metagenomic or metatranscriptome surveys

Background

Taxonomic profiling of microbial communities is often performed using small subunit ribosomal RNA (SSU) amplicon sequencing (16S or 18S), while environmental shotgun sequencing is often focused on functional analysis. Large shotgun datasets contain a significant number of SSU sequences and these can be exploited to perform an unbiased SSU--based taxonomic analysis.

Results

Here we present a new program called RiboTagger that identifies and extracts taxonomically informative ribotags located in a specified variable region of the SSU gene in a high-throughput fashion.

Conclusions

RiboTagger permits fast recovery of SSU-RNA sequences from shotgun nucleic acid surveys of complex microbial communities. The program targets all three domains of life, exhibits high sensitivity and specificity and is substantially faster than comparable programs.

     

Species Identification and Profiling of Complex Microbial Communities Using Shotgun Illumina Sequencing of 16S rRNA Amplicon Sequences

The high throughput and cost-effectiveness afforded by short-read sequencing technologies, in principle, enable researchers to perform 16S rRNA profiling of complex microbial communities at unprecedented depth and resolution. Existing Illumina sequencing protocols are, however, limited by the fraction of the 16S rRNA gene that is interrogated and therefore limit the resolution and quality of the profiling. To address this, we present the design of a novel protocol for shotgun Illumina sequencing of the bacterial 16S rRNA gene, optimized to amplify more than 90% of sequences in the Greengenes database and with the ability to distinguish nearly twice as many species-level OTUs compared to existing protocols. Using several in silico and experimental datasets, we demonstrate that despite the presence of multiple variable and conserved regions, the resulting shotgun sequences can be used to accurately quantify the constituents of complex microbial communities. The reconstruction of a significant fraction of the 16S rRNA gene also enabled high precision (>90%) in species-level identification thereby opening up potential application of this approach for clinical microbial characterization.     

Generation of multimillion-sequence 16S rRNA gene libraries from complex microbial communities by assembling paired-end illumina reads

Microbial communities host unparalleled taxonomic diversity. Adequate characterization of environmental and host-associated samples remains a challenge for microbiologists, despite the advent of 16S rRNA gene sequencing. In order to increase the depth of sampling for diverse bacterial communities, we developed a method for sequencing and assembling millions of paired-end reads from the 16S rRNA gene (spanning the V3 region; ～200 nucleotides) by using an Illumina genome analyzer. To confirm reproducibility and to identify a suitable computational pipeline for data analysis, sequence libraries were prepared in duplicate for both a defined mixture of DNAs from known cultured bacterial isolates (>1 million postassembly sequences) and an Arctic tundra soil sample (>6 million postassembly sequences). The Illumina 16S rRNA gene libraries represent a substantial increase in number of sequences over all extant next-generation sequencing approaches (e.g., 454 pyrosequencing), while the assembly of paired-end 125-base reads offers a methodological advantage by incorporating an initial quality control step for each 16S rRNA gene sequence. This method incorporates indexed primers to enable the characterization of multiple microbial communities in a single flow cell lane, may be modified readily to target other variable regions or genes, and demonstrates unprecedented and economical access to DNAs from organisms that exist at low relative abundances.     

Process Control as Ecosystem Management: Using the History of Sewage Treatment Plants to Analyze Ecosystem Management Practices

Industrial ecosystems are fruitful sites for examining ecosystem management. Sewage treatment plants, breweries, biotechnology reactors, and ethanol production plants are all ecosystems—complex biophysical systems in which communities of bacteria, yeast, fungi, and other organisms are maintained to extract services or resources. The industrial analog to ecosystem management is “process control”, where the industrial operator is the ecosystem manager. Process control is the management of a production process through the careful measurement and adjustment of its physical and chemical conditions. By analyzing the history of process control in activated sludge sewage treatment plants, I show the importance of craft knowledge in ecosystem management. Sewage treatment plant workers, through their experience in operating the plants, developed means of evaluating process conditions based on sight and smell rather than laboratory analysis. These craft techniques developed and persisted in spite of concerted efforts on the part of sanitary scientists to institute “scientific” control of the process based on laboratory analysis and models of microbial kinetics, suggesting that craft knowledge of ecosystem function can contribute to successful management. The craft knowledge of sewage plant workers is a kind of adaptive management, in which workers constantly adjust ecosystem parameters and observe the results. This approach is contrasted to “command and control” approaches to treatment plant automation, which have met with uneven success.     

Comparison of large-insert,small-insert and pyrosequencing libraries for metagenomic analysis

The development of DNA sequencing methods for characterizing microbial communities has evolved rapidly over the past decades. To evaluate more traditional, as well as newer methodologies for DNA library preparation and sequencing, we compared fosmid, short-insert shotgun and 454 pyrosequencing libraries prepared from the same metagenomic DNA samples. GC content was elevated in all fosmid libraries, compared with shotgun and 454 libraries. Taxonomic composition of the different libraries suggested that this was caused by a relative underrepresentation of dominant taxonomic groups with low GC content, notably Prochlorales and the SAR11 cluster, in fosmid libraries. While these abundant taxa had a large impact on library representation, we also observed a positive correlation between taxon GC content and fosmid library representation in other low-GC taxa, suggesting a general trend. Analysis of gene category representation in different libraries indicated that the functional composition of a library was largely a reflection of its taxonomic composition, and no additional systematic biases against particular functional categories were detected at the level of sequencing depth in our samples. Another important but less predictable factor influencing the apparent taxonomic and functional library composition was the read length afforded by the different sequencing technologies. Our comparisons and analyses provide a detailed perspective on the influence of library type on the recovery of microbial taxa in metagenomic libraries and underscore the different uses and utilities of more traditional, as well as contemporary ‘next-generation'' DNA library construction and sequencing technologies for exploring the genomics of the natural microbial world.     

Environmental microbiology through the lens of high-throughput DNA sequencing: Synopsis of current platforms and bioinformatics approaches

The incursion of High-Throughput Sequencing (HTS) in environmental microbiology brings unique opportunities and challenges. HTS now allows a high-resolution exploration of the vast taxonomic and metabolic diversity present in the microbial world, which can provide an exceptional insight on global ecosystem functioning, ecological processes and evolution. This exploration has also economic potential, as we will have access to the evolutionary innovation present in microbial metabolisms, which could be used for biotechnological development. HTS is also challenging the research community, and the current bottleneck is present in the data analysis side. At the moment, researchers are in a sequence data deluge, with sequencing throughput advancing faster than the computer power needed for data analysis. However, new tools and approaches are being developed constantly and the whole process could be depicted as a fast co-evolution between sequencing technology, informatics and microbiologists. In this work, we examine the most popular and recently commercialized HTS platforms as well as bioinformatics methods for data handling and analysis used in microbial metagenomics. This non-exhaustive review is intended to serve as a broad state-of-the-art guide to researchers expanding into this rapidly evolving field.     

RiboFR-Seq: a novel approach to linking 16S rRNA amplicon profiles to metagenomes

16S rRNA amplicon analysis and shotgun metagenome sequencing are two main culture-independent strategies to explore the genetic landscape of various microbial communities. Recently, numerous studies have employed these two approaches together, but downstream data analyses were performed separately, which always generated incongruent or conflict signals on both taxonomic and functional classifications. Here we propose a novel approach, RiboFR-Seq (Ribosomal RNA gene flanking region sequencing), for capturing both ribosomal RNA variable regions and their flanking protein-coding genes simultaneously. Through extensive testing on clonal bacterial strain, salivary microbiome and bacterial epibionts of marine kelp, we demonstrated that RiboFR-Seq could detect the vast majority of bacteria not only in well-studied microbiomes but also in novel communities with limited reference genomes. Combined with classical amplicon sequencing and shotgun metagenome sequencing, RiboFR-Seq can link the annotations of 16S rRNA and metagenomic contigs to make a consensus classification. By recognizing almost all 16S rRNA copies, the RiboFR-seq approach can effectively reduce the taxonomic abundance bias resulted from 16S rRNA copy number variation. We believe that RiboFR-Seq, which provides an integrated view of 16S rRNA profiles and metagenomes, will help us better understand diverse microbial communities.     

Gut milieu shapes the bacterial communities of invasive silver carp

Silver carp is an invasive fish present in the Gobindsagar reservoir, India and has a profound impact on aquaculture. Understanding taxonomic diversity and functional attributes of gut microbiota will provide insights into the important role of bacteria in metabolism of silver carp that facilitated invasion of this exotic species. Microbial composition in foregut, midgut, hindgut and water samples was analysed using 16S rRNA gene amplicon sequencing. The bacterial communities of water samples were distinct from gut microbiota, and unique microbial assemblages were present in different regions of gut depicting profound impact of gut environment on microflora. Proteobacteria was the most abundant phyla across all samples. Ecological network analysis showed dominance of competitive interactions within posteriors region of the gut, promoting niche specialization. Predictive functional profiling revealed the microbiota specialized in digestive functions in different regions of the gut, which also reflects the dietary profile of silver carp.